Prediction of allosteric sites and mediating interactions through bond-to-bond propensities

• Published in: Nature communications 2016-08, Vol.7 (1), p.12477-12477, Article 12477
• Main Authors: Amor, B. R. C., Schaub, M. T., Yaliraki, S. N., Barahona, M.
• Format: Article
• Language: English
• Subjects: 631/114/2411; 639/705/1041; 639/766/747; Anisotropy; Chemical bonds; Humanities and Social Sciences; multidisciplinary; NMR; Nuclear magnetic resonance; Propagation; Proteins; Science; Science (multidisciplinary)
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/ncomms12477

Allostery is a fundamental mechanism of biological regulation, in which binding of a molecule at a distant location affects the active site of a protein. Allosteric sites provide targets to fine-tune protein activity, yet we lack computational methodologies to predict them. Here we present an efficient graph-theoretical framework to reveal allosteric interactions (atoms and communication pathways strongly coupled to the active site) without a priori information of their location. Using an atomistic graph with energy-weighted covalent and weak bonds, we define a bond-to-bond propensity quantifying the non-local effect of instantaneous bond fluctuations propagating through the protein. Significant interactions are then identified using quantile regression. We exemplify our method with three biologically important proteins: caspase-1, CheY, and h-Ras, correctly predicting key allosteric interactions, whose significance is additionally confirmed against a reference set of 100 proteins. The almost-linear scaling of our method renders it suitable for high-throughput searches for candidate allosteric sites. Allostery is a key molecular mechanism underpinning control and modulation in a variety of cellular processes. Here, the authors present a method that can be used to predict allosteric sites and the mediating interactions that connect them to the active site of the protein.